
html_list <- list()

html_list[[1]] <- htmlreg(list(model_GAM_Fullcountry$fitCountry[[1]], model_GAM_Fullcountry$fitCountry[[2]], model_GAM_Fullcountry$fitCountry[[3]], model_GAM_Fullcountry$fitCountry[[4]], model_GAM_Fullcountry$fitCountry[[5]], model_GAM_Fullcountry$fitCountry[[6]], model_GAM_Fullcountry$fitCountry[[7]], model_GAM_Fullcountry$fitCountry[[8]], model_GAM_Fullcountry$fitCountry[[9]], model_GAM_Fullcountry$fitCountry[[10]], model_GAM_Fullcountry$fitCountry[[11]], model_GAM_Fullcountry$fitCountry[[12]], model_GAM_Fullcountry$fitCountry[[13]], model_GAM_Fullcountry$fitCountry[[14]], model_GAM_Fullcountry$fitCountry[[15]], model_GAM_Fullcountry$fitCountry[[16]], model_GAM_Fullcountry$fitCountry[[17]], model_GAM_Fullcountry$fitCountry[[18]], model_GAM_Fullcountry$fitCountry[[19]], model_GAM_Fullcountry$fitCountry[[20]], model_GAM_Fullcountry$fitCountry[[21]], model_GAM_Fullcountry$fitCountry[[22]], model_GAM_Fullcountry$fitCountry[[23]], model_GAM_Fullcountry$fitCountry[[24]]), 
                          custom.model.names = c(as.character(model_GAM_Fullcountry$country[c(1:24)])), custom.coef.map = list("age_grp1" = "Age group: 15-29", "age_grp2" = "Age group: 30-59", "waves.fEVS2" = "1990", "waves.fEVS3" = "1999", "waves.fEVS4" = "2008", "waves.fEVS5" = "2017", "sex" = "Gender", "EDF: s(born_adult)" = "s(Year turned 18)", "(Intercept)" = "Intercept"), caption = "")


html_list[[2]] <- htmlreg(list(model_GAM_Fullcountry$fitCountry[[25]], model_GAM_Fullcountry$fitCountry[[26]], model_GAM_Fullcountry$fitCountry[[27]], model_GAM_Fullcountry$fitCountry[[28]], model_GAM_Fullcountry$fitCountry[[29]], model_GAM_Fullcountry$fitCountry[[30]], model_GAM_Fullcountry$fitCountry[[31]], model_GAM_Fullcountry$fitCountry[[32]], model_GAM_Fullcountry$fitCountry[[33]], model_GAM_Fullcountry$fitCountry[[34]], model_GAM_Fullcountry$fitCountry[[35]], model_GAM_Fullcountry$fitCountry[[36]], model_GAM_Fullcountry$fitCountry[[37]], model_GAM_Fullcountry$fitCountry[[38]], model_GAM_Fullcountry$fitCountry[[39]], model_GAM_Fullcountry$fitCountry[[40]], model_GAM_Fullcountry$fitCountry[[41]], model_GAM_Fullcountry$fitCountry[[42]], model_GAM_Fullcountry$fitCountry[[43]], model_GAM_Fullcountry$fitCountry[[44]], model_GAM_Fullcountry$fitCountry[[45]], model_GAM_Fullcountry$fitCountry[[46]], model_GAM_Fullcountry$fitCountry[[47]], model_GAM_Fullcountry$fitCountry[[48]]), 
                          custom.model.names = c(as.character(model_GAM_Fullcountry$country[c(25:48)])), custom.coef.map = list("age_grp1" = "Age group: 15-29", "age_grp2" = "Age group: 30-59", "waves.fEVS3" = "1999", "waves.fEVS4" = "2008", "waves.fEVS5" = "2017", "sex" = "Gender", "EDF: s(born_adult)" = "s(Year turned 18)", "(Intercept)" = "Intercept"), caption = "")

html_list[[3]] <- htmlreg(list(model_GAM_Fullcountry$fitCountry[[49]], model_GAM_Fullcountry$fitCountry[[50]], model_GAM_Fullcountry$fitCountry[[51]], model_GAM_Fullcountry$fitCountry[[52]], model_GAM_Fullcountry$fitCountry[[53]], model_GAM_Fullcountry$fitCountry[[54]], model_GAM_Fullcountry$fitCountry[[55]], model_GAM_Fullcountry$fitCountry[[56]], model_GAM_Fullcountry$fitCountry[[57]], model_GAM_Fullcountry$fitCountry[[58]], model_GAM_Fullcountry$fitCountry[[59]], model_GAM_Fullcountry$fitCountry[[60]], model_GAM_Fullcountry$fitCountry[[61]], model_GAM_Fullcountry$fitCountry[[62]], model_GAM_Fullcountry$fitCountry[[63]], model_GAM_Fullcountry$fitCountry[[64]], model_GAM_Fullcountry$fitCountry[[65]], model_GAM_Fullcountry$fitCountry[[66]], model_GAM_Fullcountry$fitCountry[[67]], model_GAM_Fullcountry$fitCountry[[68]], model_GAM_Fullcountry$fitCountry[[69]], model_GAM_Fullcountry$fitCountry[[70]], model_GAM_Fullcountry$fitCountry[[71]], model_GAM_Fullcountry$fitCountry[[72]]), 
                          custom.model.names = c(as.character(model_GAM_Fullcountry$country[c(49:72)])), custom.coef.map = list("age_grp1" = "Age group: 15-29", "age_grp2" = "Age group: 30-59", "waves.fEVS3" = "1999", "waves.fEVS4" = "2008", "waves.fEVS5" = "2017", "sex" = "Gender", "EDF: s(born_adult)" = "s(Year turned 18)", "(Intercept)" = "Intercept"), caption = "")

html_list[[4]] <- htmlreg(list(model_GAM_Fullcountry$fitCountry[[73]], model_GAM_Fullcountry$fitCountry[[74]], model_GAM_Fullcountry$fitCountry[[75]], model_GAM_Fullcountry$fitCountry[[76]], model_GAM_Fullcountry$fitCountry[[77]], model_GAM_Fullcountry$fitCountry[[78]], model_GAM_Fullcountry$fitCountry[[79]], model_GAM_Fullcountry$fitCountry[[80]], model_GAM_Fullcountry$fitCountry[[81]], model_GAM_Fullcountry$fitCountry[[82]], model_GAM_Fullcountry$fitCountry[[83]], model_GAM_Fullcountry$fitCountry[[84]], model_GAM_Fullcountry$fitCountry[[85]], model_GAM_Fullcountry$fitCountry[[86]], model_GAM_Fullcountry$fitCountry[[87]], model_GAM_Fullcountry$fitCountry[[88]], model_GAM_Fullcountry$fitCountry[[89]], model_GAM_Fullcountry$fitCountry[[90]], model_GAM_Fullcountry$fitCountry[[91]], model_GAM_Fullcountry$fitCountry[[92]], model_GAM_Fullcountry$fitCountry[[93]], model_GAM_Fullcountry$fitCountry[[94]], model_GAM_Fullcountry$fitCountry[[95]], model_GAM_Fullcountry$fitCountry[[96]]), 
                          custom.model.names = c(as.character(model_GAM_Fullcountry$country[c(73:96)])), custom.coef.map = list("age_grp1" = "Age group: 15-29", "age_grp2" = "Age group: 30-59", "waves.fEVS4" = "2008", "waves.fEVS5" = "2017", "sex" = "Gender", "EDF: s(born_adult)" = "s(Year turned 18)", "(Intercept)" = "Intercept"), caption = "")

html_list[[5]] <- htmlreg(list(model_GAM_Fullcountry$fitCountry[[97]], model_GAM_Fullcountry$fitCountry[[98]], model_GAM_Fullcountry$fitCountry[[99]], model_GAM_Fullcountry$fitCountry[[100]], model_GAM_Fullcountry$fitCountry[[101]], model_GAM_Fullcountry$fitCountry[[102]], model_GAM_Fullcountry$fitCountry[[103]], model_GAM_Fullcountry$fitCountry[[104]], model_GAM_Fullcountry$fitCountry[[105]], model_GAM_Fullcountry$fitCountry[[106]], model_GAM_Fullcountry$fitCountry[[107]], model_GAM_Fullcountry$fitCountry[[108]], model_GAM_Fullcountry$fitCountry[[109]], model_GAM_Fullcountry$fitCountry[[110]], model_GAM_Fullcountry$fitCountry[[111]], model_GAM_Fullcountry$fitCountry[[112]], model_GAM_Fullcountry$fitCountry[[113]], model_GAM_Fullcountry$fitCountry[[114]], model_GAM_Fullcountry$fitCountry[[115]], model_GAM_Fullcountry$fitCountry[[116]], model_GAM_Fullcountry$fitCountry[[117]], model_GAM_Fullcountry$fitCountry[[118]], model_GAM_Fullcountry$fitCountry[[119]], model_GAM_Fullcountry$fitCountry[[120]]), 
                          custom.model.names = c(as.character(model_GAM_Fullcountry$country[c(97:120)])), custom.coef.map = list("age_grp1" = "Age group: 15-29", "age_grp2" = "Age group: 30-59", "waves.fEVS4" = "2008", "waves.fEVS5" = "2017", "sex" = "Gender", "EDF: s(born_adult)" = "s(Year turned 18)", "(Intercept)" = "Intercept"), caption = "")

html_list[[6]] <- htmlreg(list(model_GAM_Fullcountry$fitCountry[[121]], model_GAM_Fullcountry$fitCountry[[122]], model_GAM_Fullcountry$fitCountry[[123]], model_GAM_Fullcountry$fitCountry[[124]], model_GAM_Fullcountry$fitCountry[[125]], model_GAM_Fullcountry$fitCountry[[126]], model_GAM_Fullcountry$fitCountry[[127]], model_GAM_Fullcountry$fitCountry[[128]], model_GAM_Fullcountry$fitCountry[[129]], model_GAM_Fullcountry$fitCountry[[130]], model_GAM_Fullcountry$fitCountry[[131]], model_GAM_Fullcountry$fitCountry[[132]], model_GAM_Fullcountry$fitCountry[[133]], model_GAM_Fullcountry$fitCountry[[134]], model_GAM_Fullcountry$fitCountry[[135]], model_GAM_Fullcountry$fitCountry[[136]], model_GAM_Fullcountry$fitCountry[[137]], model_GAM_Fullcountry$fitCountry[[138]], model_GAM_Fullcountry$fitCountry[[139]], model_GAM_Fullcountry$fitCountry[[140]], model_GAM_Fullcountry$fitCountry[[141]], model_GAM_Fullcountry$fitCountry[[142]], model_GAM_Fullcountry$fitCountry[[143]], model_GAM_Fullcountry$fitCountry[[144]]), 
                          custom.model.names = c(as.character(model_GAM_Fullcountry$country[c(121:144)])), custom.coef.map = list("age_grp1" = "Age group: 15-29", "age_grp2" = "Age group: 30-59", "waves.fEVS4" = "2008", "waves.fEVS5" = "2017", "sex" = "Gender", "EDF: s(born_adult)" = "s(Year turned 18)", "(Intercept)" = "Intercept"), caption = "")

html_list[[7]] <- htmlreg(list(model_GAM_Fullcountry$fitCountry[[145]], model_GAM_Fullcountry$fitCountry[[146]], model_GAM_Fullcountry$fitCountry[[147]], model_GAM_Fullcountry$fitCountry[[148]], model_GAM_Fullcountry$fitCountry[[149]], model_GAM_Fullcountry$fitCountry[[150]], model_GAM_Fullcountry$fitCountry[[151]], model_GAM_Fullcountry$fitCountry[[152]], model_GAM_Fullcountry$fitCountry[[153]], model_GAM_Fullcountry$fitCountry[[154]], model_GAM_Fullcountry$fitCountry[[155]], model_GAM_Fullcountry$fitCountry[[156]], model_GAM_Fullcountry$fitCountry[[157]], model_GAM_Fullcountry$fitCountry[[158]], model_GAM_Fullcountry$fitCountry[[159]], model_GAM_Fullcountry$fitCountry[[160]], model_GAM_Fullcountry$fitCountry[[161]], model_GAM_Fullcountry$fitCountry[[162]], model_GAM_Fullcountry$fitCountry[[163]], model_GAM_Fullcountry$fitCountry[[164]], model_GAM_Fullcountry$fitCountry[[165]], model_GAM_Fullcountry$fitCountry[[166]], model_GAM_Fullcountry$fitCountry[[167]], model_GAM_Fullcountry$fitCountry[[168]]), 
                          custom.model.names = c(as.character(model_GAM_Fullcountry$country[c(145:168)])), custom.coef.map = list("age_grp1" = "Age group: 15-29", "age_grp2" = "Age group: 30-59", "waves.fEVS4" = "2008", "waves.fEVS5" = "2017", "sex" = "Gender", "EDF: s(born_adult)" = "s(Year turned 18)", "(Intercept)" = "Intercept"), caption = "")

html_list[[8]] <- htmlreg(list(model_GAM_Fullcountry$fitCountry[[169]], model_GAM_Fullcountry$fitCountry[[170]], model_GAM_Fullcountry$fitCountry[[171]], model_GAM_Fullcountry$fitCountry[[172]], model_GAM_Fullcountry$fitCountry[[173]], model_GAM_Fullcountry$fitCountry[[174]], model_GAM_Fullcountry$fitCountry[[175]], model_GAM_Fullcountry$fitCountry[[176]], model_GAM_Fullcountry$fitCountry[[177]], model_GAM_Fullcountry$fitCountry[[178]], model_GAM_Fullcountry$fitCountry[[179]], model_GAM_Fullcountry$fitCountry[[180]], model_GAM_Fullcountry$fitCountry[[181]], model_GAM_Fullcountry$fitCountry[[182]], model_GAM_Fullcountry$fitCountry[[183]], model_GAM_Fullcountry$fitCountry[[184]], model_GAM_Fullcountry$fitCountry[[185]], model_GAM_Fullcountry$fitCountry[[186]], model_GAM_Fullcountry$fitCountry[[187]], model_GAM_Fullcountry$fitCountry[[188]], model_GAM_Fullcountry$fitCountry[[189]], model_GAM_Fullcountry$fitCountry[[190]], model_GAM_Fullcountry$fitCountry[[191]], model_GAM_Fullcountry$fitCountry[[192]]), 
                          custom.model.names = c(as.character(model_GAM_Fullcountry$country[c(169:192)])), custom.coef.map = list("age_grp1" = "Age group: 15-29", "age_grp2" = "Age group: 30-59", "waves.fEVS4" = "2008", "waves.fEVS5" = "2017", "sex" = "Gender", "EDF: s(born_adult)" = "s(Year turned 18)", "(Intercept)" = "Intercept"), caption = "")

html_list[[9]] <- htmlreg(list(model_GAM_Fullcountry$fitCountry[[193]], model_GAM_Fullcountry$fitCountry[[194]], model_GAM_Fullcountry$fitCountry[[195]], model_GAM_Fullcountry$fitCountry[[196]], model_GAM_Fullcountry$fitCountry[[197]], model_GAM_Fullcountry$fitCountry[[198]], model_GAM_Fullcountry$fitCountry[[199]], model_GAM_Fullcountry$fitCountry[[200]], model_GAM_Fullcountry$fitCountry[[201]], model_GAM_Fullcountry$fitCountry[[202]], model_GAM_Fullcountry$fitCountry[[203]], model_GAM_Fullcountry$fitCountry[[204]], model_GAM_Fullcountry$fitCountry[[205]], model_GAM_Fullcountry$fitCountry[[206]], model_GAM_Fullcountry$fitCountry[[207]], model_GAM_Fullcountry$fitCountry[[208]], model_GAM_Fullcountry$fitCountry[[209]], model_GAM_Fullcountry$fitCountry[[210]], model_GAM_Fullcountry$fitCountry[[211]], model_GAM_Fullcountry$fitCountry[[212]], model_GAM_Fullcountry$fitCountry[[213]], model_GAM_Fullcountry$fitCountry[[214]], model_GAM_Fullcountry$fitCountry[[215]], model_GAM_Fullcountry$fitCountry[[216]]), 
                          custom.model.names = c(as.character(model_GAM_Fullcountry$country[c(193:216)])), custom.coef.map = list("age_grp1" = "Age group: 15-29", "age_grp2" = "Age group: 30-59", "waves.fEVS4" = "2008", "waves.fEVS5" = "2017", "sex" = "Gender", "EDF: s(born_adult)" = "s(Year turned 18)", "(Intercept)" = "Intercept"), caption = "")

html_list[[10]] <- htmlreg(list(model_GAM_Fullcountry$fitCountry[[217]], model_GAM_Fullcountry$fitCountry[[218]], model_GAM_Fullcountry$fitCountry[[219]], model_GAM_Fullcountry$fitCountry[[220]], model_GAM_Fullcountry$fitCountry[[221]], model_GAM_Fullcountry$fitCountry[[222]], model_GAM_Fullcountry$fitCountry[[223]], model_GAM_Fullcountry$fitCountry[[224]], model_GAM_Fullcountry$fitCountry[[225]], model_GAM_Fullcountry$fitCountry[[226]], model_GAM_Fullcountry$fitCountry[[227]], model_GAM_Fullcountry$fitCountry[[228]], model_GAM_Fullcountry$fitCountry[[229]], model_GAM_Fullcountry$fitCountry[[230]], model_GAM_Fullcountry$fitCountry[[231]], model_GAM_Fullcountry$fitCountry[[232]], model_GAM_Fullcountry$fitCountry[[233]], model_GAM_Fullcountry$fitCountry[[234]], model_GAM_Fullcountry$fitCountry[[235]], model_GAM_Fullcountry$fitCountry[[236]], model_GAM_Fullcountry$fitCountry[[237]], model_GAM_Fullcountry$fitCountry[[238]], model_GAM_Fullcountry$fitCountry[[239]], model_GAM_Fullcountry$fitCountry[[240]]), 
                           custom.model.names = c(as.character(model_GAM_Fullcountry$country[c(217:240)])), custom.coef.map = list("age_grp1" = "Age group: 15-29", "age_grp2" = "Age group: 30-59", "waves.fEVS4" = "2008", "waves.fEVS5" = "2017", "sex" = "Gender", "EDF: s(born_adult)" = "s(Year turned 18)", "(Intercept)" = "Intercept"), caption = "")

html_list[[11]] <- htmlreg(list(model_GAM_Fullcountry$fitCountry[[241]], model_GAM_Fullcountry$fitCountry[[242]], model_GAM_Fullcountry$fitCountry[[243]], model_GAM_Fullcountry$fitCountry[[244]], model_GAM_Fullcountry$fitCountry[[245]], model_GAM_Fullcountry$fitCountry[[246]], model_GAM_Fullcountry$fitCountry[[247]], model_GAM_Fullcountry$fitCountry[[248]], model_GAM_Fullcountry$fitCountry[[249]], model_GAM_Fullcountry$fitCountry[[250]], model_GAM_Fullcountry$fitCountry[[251]], model_GAM_Fullcountry$fitCountry[[252]], model_GAM_Fullcountry$fitCountry[[253]], model_GAM_Fullcountry$fitCountry[[254]], model_GAM_Fullcountry$fitCountry[[255]], model_GAM_Fullcountry$fitCountry[[256]], model_GAM_Fullcountry$fitCountry[[257]], model_GAM_Fullcountry$fitCountry[[258]], model_GAM_Fullcountry$fitCountry[[259]], model_GAM_Fullcountry$fitCountry[[260]], model_GAM_Fullcountry$fitCountry[[261]], model_GAM_Fullcountry$fitCountry[[262]], model_GAM_Fullcountry$fitCountry[[263]], model_GAM_Fullcountry$fitCountry[[264]]), 
                           custom.model.names = c(as.character(model_GAM_Fullcountry$country[c(241:264)])), custom.coef.map = list("age_grp1" = "Age group: 15-29", "age_grp2" = "Age group: 30-59", "waves.fEVS4" = "2008", "waves.fEVS5" = "2017", "sex" = "Gender", "EDF: s(born_adult)" = "s(Year turned 18)", "(Intercept)" = "Intercept"), caption = "")

html_list_GAM_Full_onlyInterviewed <- html_list

#Save for Shiny App
save(html_list_GAM_Full_onlyInterviewed, file = paste0(wdShinyData,"html_list_GAM_Full_onlyInterviewed.Rdata"))